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Eka Robotics nets $150M at a $1.45B valuation for robot hands that sense force

Robot dexterity startup Eka Robotics Inc. said today it has raised $150 million in new funding at a reported valuation of $1.45 billion. Eka offers an artificial intelligence model for robotic manipulation that works from force data as well as camera images. The company calls it a vision-force-action model. Force sensors in a custom gripper […] The post Eka Robotics nets $150M at a $1.45B…

Eka Robotics nets $150M at a $1.45B valuation for robot hands that sense force

Artificial intelligence firm Eka Robotics has secured $150 million in funding at a $1.45 billion valuation, focusing on robot hands that rely on force data for precise manipulation. The company's vision-force-action model utilizes force sensors in a custom gripper to monitor how tightly the hand is holding an object, enabling adjustments in grip during tasks if an object begins to slip.

Eka's technology has been demonstrated at the company's office in Cambridge, Massachusetts, where it successfully performed tasks such as screwing in light bulbs and packing chicken nuggets. The company claims its robots can handle objects weighing up to 1 kilogram, with a success rate of over 95% in picking operations per hour, surpassing the 600 operations per hour seen in human workers.

Eka is currently piloting its technology with industrial customers for pick-and-place and wire-handling applications. The gripper itself is priced under $1,000 and can withstand 5 million duty cycles. Eka aims to scale up to the 20 million duty cycles seen in standard industrial arms. Experts have praised the company's ability to adapt to various objects without retraining, though questions remain about long-term reliability on an assembly line.

Eka's founders, Tuomas Haarnoja from Google DeepMind and Pulkit Agrawal from MIT, secured the Series A investment from Andreessen Horowitz, F-Prime, Obvious Ventures, and E14 Fund, with the latter co-leading the seed round.

Written by urgent.news from SiliconANGLE's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

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